Has HIV evolved to induce immune pathogenesis?

Human immunodeficiency virus (HIV) induces a chronic generalized activation of the immune system, which plays an important role in the pathogenesis of AIDS. This ability of the virus might either be an evolved (adaptive) trait or a coincidental side effect of jumping to a new host species. We argue that selection favours the ability of HIV to induce immune activation at the local sites of infection (e.g. lymph follicles) but not at the systemic level. Immune activation increases the supply of susceptible target cells; however, mutations that increase systemic immune activation benefit all virus variants equally and are therefore selectively neutral. We thus conclude that the generalized immune acti- vation that is probably responsible for pathogenesis is probably not directly under selection

Bounds for the expected value of one-step processes

Mean-field models are often used to approximate Markov processes with large state-spaces. One-step processes, also known as birth-death processes, are an important class of such processes and are processes with state space $\{0,1,\ldots,N\}$ and where each transition is of size one. We derive explicit bounds on the expected value of such a process, bracketing it between the mean-field model and another simple ODE. Our bounds require that the Markov transition rates are density dependent polynomials that satisfy a sign condition. We illustrate the tightness of our bounds on the SIS epidemic process and the voter model.Comment: 14 pages, 4 figures, revise

Analyzing Fiscal Policy and Growth with a Calibrated Macro Model

CEE countries experience a catching up period in economic growth while preparing for accession to the European Union. In several countries we experience an expenditure boom arising either from exuberant expectations of consumers towards EU or EM or a fiscal deficit usually underpinned by an argument that a reallocation of total consumption at the expense of the future is a result of intertemporal optimization. The paper analyses whether this argument is justifiable. The key factors that influence the intertemporal trade-off are country risk and externalities from foreign direct investments. High indebtedness increases macroeconomic risk and discourages investments. If investment externalities exist the investment gap may cause high output loss. With careful calibration of the parameters determining the risk premium and the external effects of FDI the model predicts a 20% annual return of fiscal austerity at the macro level. This number is too high to be justifiable by any reasonable rate of time preference.Catching-up, Risk Premium, FDI, Consumption boom, Simulation.

SIS epidemic propagation on hypergraphs

Mathematical modeling of epidemic propagation on networks is extended to hypergraphs in order to account for both the community structure and the nonlinear dependence of the infection pressure on the number of infected neighbours. The exact master equations of the propagation process are derived for an arbitrary hypergraph given by its incidence matrix. Based on these, moment closure approximation and mean-field models are introduced and compared to individual-based stochastic simulations. The simulation algorithm, developed for networks, is extended to hypergraphs. The effects of hypergraph structure and the model parameters are investigated via individual-based simulation results

Role of hexagonal boron nitride in protecting ferromagnetic nanostructures from oxidation

Ferromagnetic contacts are widely used to inject spin polarized currents into non-magnetic materials such as semiconductors or 2-dimensional materials like graphene. In these systems, oxidation of the ferromagnetic materials poses an intrinsic limitation on device performance. Here we investigate the role of ex-situ transferred chemical vapour deposited hexagonal boron nitride (hBN) as an oxidation barrier for nanostructured cobalt and permalloy electrodes. The chemical state of the ferromagnets was investigated using X-ray photoemission electron microscopy owing to its high sensitivity and lateral resolution. We have compared the oxide thickness formed on ferromagnetic nanostructures covered by hBN to uncovered reference structures. Our results show that hBN reduces the oxidation rate of ferromagnetic nanostructures suggesting that it could be used as an ultra-thin protection layer in future spintronic devices.Comment: 7 pages, 6 figure

Differential equation approximations of stochastic network processes: an operator semigroup approach

The rigorous linking of exact stochastic models to mean-field approximations is studied. Starting from the differential equation point of view the stochastic model is identified by its Kolmogorov equations, which is a system of linear ODEs that depends on the state space size ($N$) and can be written as $\dot u_N=A_N u_N$. Our results rely on the convergence of the transition matrices $A_N$ to an operator $A$. This convergence also implies that the solutions $u_N$ converge to the solution $u$ of $\dot u=Au$. The limiting ODE can be easily used to derive simpler mean-field-type models such that the moments of the stochastic process will converge uniformly to the solution of appropriately chosen mean-field equations. A bi-product of this method is the proof that the rate of convergence is $\mathcal{O}(1/N)$. In addition, it turns out that the proof holds for cases that are slightly more general than the usual density dependent one. Moreover, for Markov chains where the transition rates satisfy some sign conditions, a new approach for proving convergence to the mean-field limit is proposed. The starting point in this case is the derivation of a countable system of ordinary differential equations for all the moments. This is followed by the proof of a perturbation theorem for this infinite system, which in turn leads to an estimate for the difference between the moments and the corresponding quantities derived from the solution of the mean-field ODE

A központi idegrendszer validált célfehérjéi: a funkcionálisan aktív konformációk modellezése = Validated target proteins of the CNS: modeling functionally active conformations

A központi idegrendszeri jelátvitelben résztvevő célfehérjék és az MTA KK BKI Neurokémiai Osztályán kísérletesen vizsgált vegyületek között fellépő kötődési kölcsönhatások vizsgálatát számítógépes molekulamodellezéssel és dokkolási eljárással végeztük. A glutaminsav receptorok (GluR) és transzporterek szerepe kulcsfontosságú a serkentő jelátvitelben. Az ioncsatornát formáló (iGluR) valamint a hét transzmembrán szakaszt tartalmazó (7TM) metabotróp (mGluR) receptor altípusok nagyfelbontású kristályos szerkezete ismeretében dokkolással határoztuk meg a ligandumok illeszkedését az iGluR2 valamint az mGluR1 receptorok extracelluláris kötődoménjébe. A 7TM receptorok membránba ágyazott részének nagyfelbontású szerkezete csupán a rodopszin molekula esetén ismert. Ennek alapján a szomatosztatin 1 receptorról homológia modellt készítettünk és a tumorgátló hatású TT-232 ciklopeptid dokkolása után a kötődésben résztvevő aminosavakat vizsgáltuk. A fototranszdukciós kaszkádban résztvevő foszfodiészteráz 6 (PDE6) enzim katalitikus inhibitorai hatására paradox fényválasz növekedést mutattunk ki. Elektrofiziológiai méréseink és dokkolási eredményeink szerint a vizsgált inhibitorok a katalitikus cGMP hidrolízist szabályozó PDE6 gamma alegység gátlóhatását akadályozzák. E célfehérje-ligandum kötődési kölcsönhatások molekuláris meghatározottságának megismerése jelentősen járult hozzá fontos célfehérjék működésének megértéséhez, így a vizsgált drogok hatásmechanizmusának feltárásához. | Binding interactions between target molecules of the central nervous system and their ligands have been studied by molecular modeling and docking methods. These ligands were also tested experimentally at the Neurochemistry Department of CRC HAS. Glutamate receptors and transporters play a key role in excitatory signal transduction. High-resolution crystal structures of the extracellular ligand-binding domains of ionotropic glutamate receptors (iGluR) and seven transmembrane helix (7TM) containing metabotropic glutamate receptor (mGluR) subtypes were recently disclosed, therefore position of ligands could be determined by structure-based molecular docking. The full structure of a 7TM receptor is only available for bovine rhodopsin. Based on this structure a homology model for somatostatin receptor 1 was built and TT-232, a cyclopeptide with antitumor activity was docked and binding crevice residues were delineated. A key element of the phototransduction cascade, phosphodiesterase 6 (PDE6) and its interaction with catalytic site inhibitors was also studied. Electrophysiological measurements revealed a paradoxical increase in light response after inhibitor application. Molecular docking showed that the effect is due to a competition between inhibitors and the regulatory PDE6 gamma subunit residues. Results of these studies contribute to future understanding of protein-drug interactions and help to gain insight into molecular mechanisms of drug action